جست‌وجوی استاد و پژوهشگر

• Optimisation
• Artificial Intelligence
• Machine Learning
• +۲ مورد دیگر

Dr. Thao Duong serves as a Senior Lecturer at the School of Information Technology, Murdoch University, where she contributes to both teaching and research in computer science with a focus on computational problem-solving methodologies. Education Background Ph.D. in Computer Science from Griffith University, Queensland Research Expertise Her work centers on optimisation (particularly combinatorial optimisation and satisfiability problems), artificial intelligence , and machine learning , with significant contributions to data science and data analytics . Dr. Duong develops advanced algorithms for complex decision-making systems, bridging theoretical computer science with practical applications in data engineering. Professional Recognition Best paper award at the Australasian Joint Conference on Artificial Intelligence (2013) Academic Contributions She maintains an active publication record in premier venues including AAAI, IJCAI, and EJOR, though specific student supervision details and grant funding information are not documented in available sources. No current laboratory affiliations or collaborative research teams are explicitly referenced in her professional profile.

Jingling Xueمشاهده پروفایل

استاد

• Programming Languages
• Compilers
• Program Analysis
• +۵ مورد دیگر

Jingling Xue is a Scientia Professor at the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Sydney, Australia. As an IEEE Fellow of the Computer Society, he leads the Programming Languages and Compilers research group, focusing on practical applications of compiler optimization and program analysis techniques. His work bridges theoretical foundations with real-world software systems, particularly in developing open-source tools for large-scale program analysis. Professor Xue received his B.Eng and M.Eng degrees from Tsinghua University in 1984 and 1987, respectively, followed by a PhD from the University of Edinburgh in 1992. His academic journey has established him as a leading figure in programming languages and compiler technology. Xue's research spans programming languages, compiler technology, and program analysis with emphasis on practical relevance. His current projects include compiler techniques for improving parallelism and locality, pointer/alias analysis for million-line-scale programs, and static/dynamic analysis for detecting bugs and security vulnerabilities in real-world applications like web browsers and Android apps. His group actively develops open-source tools to support scientific replicability and reproducibility in these areas. His recent publications demonstrate a strong focus on applying program analysis techniques to modern challenges including AI compilers, homomorphic encryption, security vulnerability detection, and graph processing systems. The work shows evolution from traditional compiler optimization to addressing emerging domains like privacy-preserving computation and deep learning systems while maintaining rigorous theoretical foundations. Scientific Awards: Best Paper Award at CGO'13 Best Paper Award at CGO'16 Distinguished Paper Award at ECOOP'16 Distinguished Paper Award at ICSE'18 Distinguished Paper Award at ISSTA'19 Distinguished Paper Award at ASE'19 Distinguished Artifact Award at ISSTA'23 Best Artifact Award at FSE'23 Distinguished Paper Award at ASE'23 Test-of-Time Award at CGO'21 Professor Xue has successfully supervised 30 PhD students to completion, many of whom now work as professors or researchers in academia and industry. He has served as Program Chair for major conferences including LCTES'13, CC'18, CGO'20, and General Chair for LCTES'20. His group currently focuses on memory safety in Rust, smart contract analysis, AI compilers, compilation for privacy-preserving computation, and adversarial attacks in deep learning. The Programming Languages and Compilers group maintains strong connections with industry partners, translating theoretical advances into practical tools for real-world software development challenges. Their work on pointer analysis, memory safety, and compiler optimizations continues to influence both academic research and industrial practice.

Yinglong Heمشاهده پروفایل

مدرس

• Intelligent Transportation Systems
• Energy Management & Decarbonisation
• Vehicle & Powertrain Dynamics
• +۷ مورد دیگر

Dr. Yinglong He is a Lecturer in Automated Electrified Transport (AcT) Systems at the School of Mechanical Engineering Sciences, University of Surrey, UK, and an Honorary Assistant Professor at the School of Engineering, University of Birmingham. His research focuses on intelligent transportation systems, energy management, vehicle dynamics, and AI-driven optimisation. He has held positions including Postdoctoral Research Associate at the University of Cambridge and Technology Expert at the European Commission's Joint Research Centre (JRC). Research interests include autonomous vehicle control, traffic simulation, hybrid/electric vehicle dynamics, and sustainable transport solutions. Notable contributions include advancing microscopic traffic models for automated vehicles and optimising energy systems for hybrid powertrains. His work integrates machine learning, multi-agent systems, and data-driven approaches to address challenges in transport decarbonisation and safety. Recent publications highlight advancements in hybrid vehicle dynamics simulation, lithium-air battery modelling, and energy mapping of urban buildings. He has received the Chinese Government Award for Outstanding Self-Financed Students (2022) and is a Fellow of the Institute for Sustainability (IfS). His expertise spans interdisciplinary collaborations in automotive engineering, energy systems, and smart infrastructure.

Cormac Lucasمشاهده پروفایل

مدرس ارشد

• Mathematical Optimisation
• Stochastic Optimisation
• Asset and Liability Management (ALM)
• +۵ مورد دیگر

Dr. Cormac Lucas is a Senior Lecturer in the Department of Mathematics at Brunel University London, affiliated with the College of Engineering, Design and Physical Sciences. His work bridges mathematical optimization with practical applications in finance and operations management. Lucas specializes in Mathematical Optimisation Stochastic Optimisation Asset and Liability Management (ALM) Risk Analytics Portfolio Optimization Supply Chain Planning Under Uncertainty His research combines theoretical advancements with industrial projects, such as US Coast Guard Cutter Scheduling, Insight Investment's ALM, and Unilever's Natural Oil Buying Policy. Recent publications (2013–2024) highlight his focus on Portfolio Rebalancing with Transaction Costs Scenario Generation for Stochastic Programming Heuristic Algorithms for Cardinality Constraints Queuing Systems with Standby Servers Robust Supply Chain Planning Financial Derivative Modeling These works utilize methods like Variable Neighbourhood Search, Differential Evolution, and Lagrangian Relaxation. Email: cormac.lucas@brunel.ac.uk

• Multi-objective optimisation
• Evolutionary computation
• Explainable artificial intelligence
• +۴ مورد دیگر

Dr David Walker is a Senior Lecturer in Computer Science at the University of Exeter and a member of the Institute for Data Science and Artificial Intelligence . He also contributes to the Environmental Intelligence @Exeter research network. Education: PhD in Computer Science, University of Exeter (2008–2013) BSc (Hons) in Computer Science, University of Exeter (2004–2007) Research Interests Dr Walker’s work sits at the intersection of multi-objective optimisation , evolutionary computation , explainable AI and hyper-heuristics . He develops algorithms and visual analytics that help engineers and scientists understand complex optimisation landscapes, with recent emphasis on renewable-energy planning (especially offshore wind farms) and trustworthy AI systems. Publication Trends Between 2022 and 2025 he produced a prolific stream of articles on explainable optimisation , many-objective wind-farm design and visual analytics for evolutionary algorithms . These works combine rigorous algorithmic innovation with real-world case studies, demonstrating a clear trajectory toward transparent, human-centred AI for engineering decision-making. Scientific Awards No specific awards or fellowships are mentioned in the provided material. Advising & Funding No explicit list of PhD students, post-docs or grant awards is supplied. Laboratory & Teams Dr Walker is affiliated with the Institute for Data Science and Artificial Intelligence and the Environmental Intelligence @Exeter network, indicating collaborative, interdisciplinary research environments.

• Combinatorial Optimization
• Operations Research
• Stochastic Programming
• +۵ مورد دیگر

Hanyu Gu is a Senior Lecturer in the School of Mathematical and Physical Sciences at the University of Technology Sydney (UTS), part of the Faculty of Science. He holds a PhD in Power Engineering and Automation from Shanghai Jiao Tong University (1999) and has extensive industry experience in telecommunications, airline optimization, and mining. His research focuses on combinatorial optimization, decomposition methods, stochastic programming, and machine learning applications. Notable awards include second place in the 2020 ROADEF competition. He collaborates with institutions like the UTS Transportation Research Centre and has contributed to projects such as optimisation engines for airline management and underground mining algorithms. Current research explores hybrid algorithms, Bayesian optimisation, and scheduling under uncertainty. Education: Bachelor in Industrial Automation, Shanghai Jiao Tong University (1994) Master in Control Theory and Application, Shanghai Jiao Tong University (1997) PhD in Power Engineering and Automation, Shanghai Jiao Tong University (1999) Industry Experience: ZTE (1999–2001): Senior Wireless Communication Engineer CTI, Melbourne (2007–2011): Airline Management Optimisation Researcher NICTA (2011–2013): Underground Mining Optimisation Researcher Grants: ARC Linkage Project LP0883855 (2008–2012): Developed optimisation tools for transportation crewing, valued at $840,000. Research interests span decomposition methods for large-scale problems (e.g., airline scheduling), stochastic programming for resource sharing, and hybridisation of mathematical programming with constraint programming. Recent work includes Bayesian optimisation for knapsack problems and relax-and-solve algorithms for project scheduling. His articles frequently address optimisation in logistics, healthcare, and transportation, emphasizing practical industry applications and algorithmic innovation. Awards: Second place in the ROADEF 2020 competition for maintenance planning solutions. Advising & Grants: Supervises Masters and PhD students in operations research and optimisation. Collaborates with Ausgrid, UGL, and ANC on optimisation projects (e.g., employee training timetabling, logistics). Active in the Optimisation Group of UTS Transportation Research Centre, he bridges academic research with real-world challenges in scheduling, logistics, and resource management. Ongoing efforts include advancing metaheuristics and integrating machine learning with traditional optimisation techniques.

Franjo Ceceljaمشاهده پروفایل

استاد

• Systems Engineering for Energy and Industrial Applications
• Optimisation and Decision Making
• Knowledge Modelling (Ontology Engineering)
• +۳ مورد دیگر

Dr. Franjo Cecelja is a Reader in the School of Chemistry and Chemical Engineering at the University of Surrey. He holds a Dipl. Eng. from the University of Zagreb, an M.Sc. from Cranfield Institute of Technology, and a Ph.D. from Brunel University. His research focuses on systems engineering for energy and industrial applications, optimization, decision making, and semantic technologies. He has led projects such as the FP7 (Marie Curie LTN) initiative on renewable energy systems engineering (£425k, 2013–2018). His work spans ontology engineering applications in biorefining, waste valorization, and sustainable processing. Notable contributions include semantic frameworks for model and data integration in biorefineries and decision support systems for industrial symbiosis. Education: Ph.D., Brunel University (Optical Sensors for Electric Fields) M.Sc., Cranfield Institute of Technology (Control & Signal Processing) Dipl. Eng., University of Zagreb (Aerospace Technology) His research interests integrate ontology engineering with process systems engineering to address challenges in biorefining, industrial symbiosis, and sustainable resource management. Recent publications emphasize semantic technologies for waste valorization, PFAS treatment, and decision-making frameworks in biorefining. Dr. Cecelja’s FP7 project demonstrated leadership in renewable energy systems, leveraging semantic networking facilities and value chain optimization. His work bridges academic research with industrial applications, emphasizing circular economy principles and model-driven decision support. Labs/Teams: His research is conducted within the University of Surrey’s School of Chemistry and Chemical Engineering facilities, collaborating with interdisciplinary teams on biorefining and process systems engineering.

• Operational Research
• Healthcare Analytics
• Retail Analytics
• +۳ مورد دیگر

Siamak Naderi is an Assistant Professor of Operational Research and Analytics in the ISMA Group at Warwick Business School (WBS), joined since December 2020. His research focuses on Healthcare Analytics, Retail Analytics, and large-scale optimization methods for complex decision-making environments. He holds a PhD and Master's from Sabanci University and a Bachelor's from the University of Tehran. Education PhD and MSc in Industrial Engineering, Sabanci University, Istanbul BSc in Industrial Engineering, University of Tehran, Iran His research has been funded by EPSRC and published in top journals like International Journal of Production Economics and International Journal of Production Research. Current teaching includes Mathematical Programming, Business Analytics, Data Management, and Generative AI applications across undergraduate, master's, and doctoral programs. Research Trends : Recent work emphasizes supply chain optimization in fast-fashion retail, healthcare system modeling under budget constraints, and heuristic solutions for operational efficiency. His articles blend theoretical optimization with real-world applications in retail and healthcare sectors. Teaching & Mentoring : Actively mentors students across BSc, MSc, and PhD programs in analytics and operational research. Teaches advanced modules like Pricing Analytics, Optimisation Models, and AI applications. Labs & Collaborations : Part of the ISMA Group at WBS, focusing on data-driven analytics for business and healthcare sectors. Collaborates on EPSRC-funded healthcare analytics projects.

David Harveyمشاهده پروفایل

استاد

• Computational Number Theory
• Arithmetic Geometry
• Fast Polynomial Arithmetic
• +۳ مورد دیگر

Professor David Harvey is a faculty member at the School of Mathematics and Statistics within the University of New South Wales (UNSW), where he has held positions ranging from Courant Instructor to his current professorship. He is also a Fellow of the Australian Mathematical Society . Ph.D. in Mathematics (Harvard University, 2008) B.Sc. in Mathematics with First Class Honours and University Medal (UNSW, 2002) Harvey's research focuses on computational number theory and arithmetic geometry , with emphasis on fast polynomial and integer arithmetic algorithms. His work includes groundbreaking advancements in O(n log n) complexity for integer multiplication, leveraging techniques such as Fast Fourier Transforms , lattice reduction , and p-adic cohomology for zeta function computations. His publications from 2018–2024 demonstrate expertise in algorithm design for problems in number theory , algebraic geometry , and cryptography , with recurring themes of computational efficiency , finite field arithmetic , and polynomial operations . 2022 N.G. de Bruijn Medal (shared) 2019 Australian Mathematical Society Medal 2016 Journal of Complexity Best Paper Award Harvey has led significant research grants including the ARC Future Fellowship (2017–2021) and the ARC Discovery Project , focusing on zeta function algorithms and point-counting on algebraic surfaces . He co-organizes the UNSW Number Theory Seminar.

Agni Orfanoudakiمشاهده پروفایل

دانشیار

• Operations Research
• Machine Learning
• Healthcare Operations
• +۶ مورد دیگر

Agni Orfanoudaki serves as an Associate Professor of Operations Management at the University of Oxford's Saïd Business School and holds a Fellowship in Management Studies at Exeter College. She concurrently maintains a visiting scholar position at Harvard Kennedy School as a Harvard Data Science Initiative fellow. Her academic journey includes a Ph.D. in Operations Research from MIT and undergraduate studies at Athens University of Economics and Business. Her research focuses on developing machine learning algorithms to address real-world data imperfections—including missing values, censored observations, and unobserved counterfactuals—with applications in healthcare and insurance. Key contributions include predictive models for cardiovascular/cerebrovascular diseases and COVID-19 patient care, alongside pioneering the field of algorithmic insurance through quantitative frameworks for litigation risk assessment of ML models. She emphasizes interpretability and system design for seamless healthcare integration. Orfanoudaki leads the Data Driven Decisions Lab (3DL), collaborating with eight+ US/European hospitals, major medical societies, and international reinsurers. Her teaching spans MBA/EMBA Technology and Operations Management courses and the Oxford AI Ethics, Regulation and Compliance Programme, supplemented by machine learning instruction for Exeter College undergraduates.

Aliesha Jane Hvalaمشاهده پروفایل

پژوهشگر

• Environmental Science
• Remote Sensing
• Artificial Intelligence
• +۳ مورد دیگر

Aliesha Jane Hvala is a researcher affiliated with the North Australia Centre for Autonomous Systems (NACAS) within the Faculty of Science and Technology. She holds a Bachelor of Environmental Science and a Bachelor of Science (Honours) from Charles Darwin University. Her research focuses on environmental remote sensing, specifically leveraging Remotely Piloted Aircraft Systems (RPAS) and AI to address marine debris challenges and conservation efforts. She leads the HDR Project 'Optimising coastal marine debris management through RPAS remote sensing and AI-enabled solutions'. Education: BSc Environmental Science (Charles Darwin University), BSc(Hons) First Class (Charles Darwin University). Key Projects: Developing operational frameworks for marine debris monitoring using drones and AI in collaboration with Anindilyakwa Land and Sea Rangers. Her work integrates drone technology with biotelemetry to enhance wildlife detection and supports Indigenous Ranger groups in conservation training. Recent publications include studies on drone healthcare delivery systems and wildlife monitoring methodologies.

• Polyhedral combinatorics
• Extended formulations
• Combinatorial optimization
• +۲ مورد دیگر

Samuel Fiorini is Associate Professor in the Department of Mathematics at the Université libre de Bruxelles (ULB) , member of the Algebra and Combinatorics group (CP 216). His research centres on polyhedral combinatorics, extended formulations, combinatorial optimisation and approximation algorithms , with frequent overlap into structural graph theory. Research in depth: Fiorini’s work explores how high-dimensional polytopes can sometimes be expressed compactly through extended formulations, proving exponential lower bounds when they cannot. He has contributed new approximation algorithms for classical problems such as vertex cover, clique transversal and odd-cycle packing, and has advanced the understanding of sorting and entropy in partially ordered sets. His papers often combine tools from graph minors, communication complexity and polyhedral theory. Scientific recognition: Best Paper Award, 44th ACM Symposium on Theory of Computing (STOC 2012) Programme committees: FOCS, IPCO, APPROX, STACS, WAOA Organiser, Sixth Cargese Workshop on Combinatorial Optimization Advising & grants: He currently supervises PhD students Carole Muller and Matthew Drescher and has mentored six completed PhDs as well as more than a dozen post-doctoral researchers. His group has been supported by an ERC starting grant and other national and international projects focusing on polyhedral approaches to hard optimisation problems. Lab & team: Fiorini leads a vibrant team within the Algebra and Combinatorics cluster at ULB, maintaining active collaborations with researchers worldwide and hosting frequent visitors working on discrete optimisation and polyhedral combinatorics.

Sven Scheweمشاهده پروفایل

استاد

• Automata Theory
• Game Theory
• Formal Verification
• +۱۲ مورد دیگر

Sven Schewe is a Professor in the Department of Computer Science at the University of Liverpool, affiliated with the School of Electrical Engineering, Electronics and Computer Science. He leads the AI Section and is a founding member and former leader of the Verification Group. He also has secondary affiliations with the Algorithms, Complexity Theory and Optimisation Group and the Institute for Risk and Uncertainty. Research Interests: His research centers on automata theory and game theory, particularly their applications in the verification and synthesis of reactive and safety-critical systems. He investigates infinite-duration games, automata over infinite words and trees, and develops algorithms and tools for automated verification, synthesis, and learning of optimal control strategies. His work extends to reinforcement learning with formal guarantees, cyber-physical systems, and AI safety. Recent Research Trends: His recent publications demonstrate a strong integration of formal methods with machine learning, particularly in adversarial training, neural network robustness, and model-free reinforcement learning under omega-regular objectives. He also applies formal reasoning to interdisciplinary domains such as chemical space exploration and materials science. Scientific Awards: Finalist for the ERCIM Cor Baayen Award 2010 Dr. Eduard Martin Preis 2009 GI Dissertation Award 2008 Advising and Grants: He actively supervises numerous PhD students and postdoctoral researchers. He is Principal Investigator (PI) or Co-Investigator (CI) on multiple major grants, including EPSRC Programme Grants, Royal Society Fellowships, and Horizon Europe projects. His funded research spans topics such as game theory, verification, synthesis, reinforcement learning, and risk analysis. He has hosted visiting researchers and collaborated internationally with institutions in Germany, France, India, Taiwan, and the US. Labs and Teams: He co-founded and led the Verification Group and previously led the AI Section at the University of Liverpool. These groups focus on formal methods, automata, games, and their applications in AI and safety-critical systems.

Holger H. Hoosمشاهده پروفایل

استاد

• Human-centred AI
• AI for Good
• AI for All
• +۶ مورد دیگر

Holger H. Hoos is the Alexander von Humboldt Professor of AI at RWTH Aachen University (Germany), Professor of Machine Learning at Universiteit Leiden (Netherlands), and Adjunct Professor of Computer Science at the University of British Columbia (Canada). He also serves as Faculty Associate at the Peter Wall Institute for Advanced Studies, UBC. Affiliations: RWTH Aachen University, Universiteit Leiden, University of British Columbia Research interests include methodological and technological advances in human-centred AI, AI for Good, and AI for All. His work focuses on improving AI efficiency and robustness, automated algorithm design (notably Programming by Optimisation and AutoML ), and interdisciplinary applications of AI. He leads the AI Center at RWTH Aachen. Scientific leadership includes roles as president of the European Association for AI (EurAI), co-founder of CLAIRE (now CAIRNE), and past president of the Canadian Association for Artificial Intelligence (CAIAC). His book on Stochastic Local Search (with Thomas Stützle) remains a foundational text in the field. Awards and recognition include: Alexander von Humboldt Professorship (2021) Fellow of ACM, AAAI, and EurAI German AI Innovation Prize (2021) for CLAIRE and ELLIS

Rakesh Nandiمشاهده پروفایل

پژوهشگر ارشد

• Queueing systems
• Stochastic modelling
• Numerical optimisation
• +۱ مورد دیگر

Rakesh Nandi is a Research Fellow at the Aviation Studies Institute (ASI) of Singapore University of Technology and Design (SUTD). He previously held a research fellowship under Dr. Shrutivandana Sharma at the Engineering Systems and Design (ESD) school at SUTD. His work focuses on optimizing and analyzing air traffic networks, with projects such as Network Capacity and Network Collaboration under Professor Peter Jackson. Rakesh earned his Ph.D. in Mathematics from National Institute of Technology Raipur (2020) and an M.Sc. in Applied Mathematics from Guru Ghasidas University (2013). His research interests span queueing systems , stochastic modeling , numerical optimization , and network modeling/scheduling . He collaborates on projects requiring advanced computational and analytical methods for discrete-time queueing systems. His recent publications (2018–2022) emphasize queueing theory applications, stochastic processes, and optimization in discrete-time systems. Key topics include D-BMAP/G/1 queues, GI/D-MSP queue analysis, and N-policy control strategies. While no scientific awards are listed, Rakesh demonstrates active research in operations research and applied mathematics. He has no documented advisees or grants mentioned. He contributes to interdisciplinary teams at ASI and ESD, focusing on aviation systems and network efficiency.